The semiconductor industry is evolving with quantum imaging and AI-driven technologies, enhancing defect detection and ...
A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), in collaboration with Dr. Jaemin Wang and Prof. Dierk Raabe of the ...
Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...
Industrial quality inspection plays a critical role in manufacturing, from ensuring the reliability of electronics and vehicles to preventing costly failures in aerospace and energy systems.
Existing defect detection tools using ultrasound rely on phased array ultrasound. In this method, many transducers are pointed in the same direction to generate an image of that specific area. This ...
Abstract: Concurrency defects such as race conditions, deadlocks, and improper synchronization remain a critical challenge in developing reliable OpenMP-based parallel applications. Traditional static ...
Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...
Abstract: This work proposes the use of machine learning-based techniques for enhanced testability and performance calibration of an industrial 79-GHz power amplifier (PA) designed for an automotive ...
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